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| Content Provider | Springer Nature Link |
|---|---|
| Author | Giletto, Claudia M. Echeverría, Hernán E. |
| Copyright Year | 2016 |
| Abstract | In-season N applications to processing potato crops may increase profits and improve N fertilizer use efficiency. The objective of our study was to evaluate indices to predict the differential economic optimum N rate (dEONR) using a SPAD 502 chlorophyll meter, a Crop Circle ACS-210 (CC), and a Green Seeker 506 (GS). Additionally, algorithms were developed to determine N fertilizer variable rates. The relative chlorophyll meter reading (RCM), the relative chlorophyll index (RCI), and the relative normalized differential vegetative index (RNDVI) were calculated using the mean sensor value divided by the value determined in plots with the highest N rate within each site-year. The relationship between relative indices and dEONR was evaluated by fitting quadratic and quadratic-plateau regression models. The canopy chlorophyll indices (RCM and RCI) were significantly associated with dEONR during the growing season (R$^{2}$ = 0.48, 0.22 at 40 days after planting (DAP), R$^{2}$ = 0.28, 0.73 at 60 DAP, R$^{2}$ = 0.62, 0.82 at 80 DAP, R$^{2}$ = 0.58, 0.83 at 100 DAP for RCM and RCI, respectively). The canopy biomass index (RNDVI) was significantly associated with dEONR only at tuber bulking (R$^{2}$ = 0.51, 0.85 at 80 DAP and R$^{2}$ = 0.48, 0.51 at 100 DAP, for GS and CC, respectively). The canopy chlorophyll indices performed better than the canopy biomass indices in measuring N stress. The optical sensor CC was better than the GS in predicting N stress because it measures the RNDVI and the RCI in a single reading.La aplicación de N durante el ciclo del cultivo de papa para industria puede aumentar los beneficios y mejorar la precisión de la fertilización nitrogenada. El objetivo de nuestro estudio fue evaluar los índices para predecir la tasa económica óptima N (dDOEN) utilizando el medidor de clorofila SPAD 502 (MC), el Crop Circle ACS-210 (CC), y el Green Seeker 506 (GS). Además, se han desarrollado algoritmos para determinar dosis variable de N. Lecturas relativas del medidor de clorofila (RMC), índice de clorofila relativo (RCI) y el índice de vegetación diferencial normalizado relativo (RNDVI) se calcula utilizando el valor medio del sensor dividido por el valor determinado en las parcelas con la tasa más elevada de N dentro de cada sitio-año. La relación entre los índices relativos y dDOEN se evaluó mediante modelos de regresión cuadrático (Q) y cuadrática-meseta (QP). Los índices relativos de la clorofila del canopeo (RMC y RCI) se asociaron significativamente con dDOEN durante la estación de crecimiento (R$^{2}$ = 0,48, 0,22 a los 40 días después de la siembra (DDS), R$^{2}$ = 0,28, 0,73 a 60 DAP, R$^{2}$ = 0,62, 0,82 a 80 DAP, R$^{2}$ = 0,58, 0,83 a 100 DAP de RCM y RCI, respectivamente). El índice de biomasa del canopeo (RNDVI) se asoció significativamente con dDOEN sólo en la etapa de llenado de tubérculos (R$^{2}$ = 0,51, 0,85 a 80 DAP y R$^{2}$ = 0,48, 0,51 a 100 DAP, para GS y CC, respectivamente). Los índices de clorofila del canopeo tuvieron un mejor desempeño que los índices de biomasa del canopeo en la determinación del estrés de N. El sensor óptico CC fue mejor que los GS en la predicción de estrés N, ya que mide el NDVI y el IC en una sola lectura. |
| Starting Page | 253 |
| Ending Page | 263 |
| Page Count | 11 |
| File Format | |
| ISSN | 1099209X |
| Journal | American Potato Journal |
| Volume Number | 93 |
| Issue Number | 3 |
| e-ISSN | 18749380 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2016-03-01 |
| Publisher Institution | Potato Association of America |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Chlorophyll meter Chlorophyll index Normalized differential vegetative index Plant Sciences Agriculture Plant Genetics & Genomics Plant Breeding/Biotechnology Plant Pathology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Plant Science Agronomy and Crop Science |
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